Storage and retrieval of microarray data and open source microarray database software

Microarray technology has been widely adopted by researchers who use both home-made microarrays and microarrays purchased from commercial vendors. Associated with the adoption of this technology has been a deluge of complex data, both from the microarrays themselves, and also in the form of associated meta data, such as gene annotation information, the properties and treatment of biological samples, and the data transformation and analysis steps taken downstream. In addition, standards for annotation and data exchange have been proposed, and are now being adopted by journals and funding agencies alike. The coupling of large quantities of complex data with extensive and complex standards require all but the most small-scale of microarray users to have access to a robust and scaleable database with various tools. In this review, we discuss some of the desirable properties of such a database, and look at the features of several freely available alternatives.     

Open source software for the analysis of microarray data

DNA microarray assays represent the first widely used application that attempts to build upon the information provided by genome projects in the study of biological questions. One of the greatest challenges with working with microarrays is collecting, managing, and analyzing data. Although several commercial and noncommercial solutions exist, there is a growing body of freely available, open source software that allows users to analyze data using a host of existing techniques and to develop their own and integrate them within the system. Here we review three of the most widely used and comprehensive systems, the statistical analysis tools written in R through the Bioconductor project (http://www.bioconductor.org), the Java-based TM4 software system available from The Institute for Genomic Research (http://www.tigr.org/software), and BASE, the Web-based system developed at Lund University (http://base.thep.lu.se).     

FLIM-FRET analyzer: open source software for automation of lifetime-based FRET analysis

Background

Despite the broad use of FRET techniques, available methods for analyzing protein-protein interaction are subject to high labor and lack of systematic analysis. We propose an open source software allowing the quantitative analysis of fluorescence lifetime imaging (FLIM) while integrating the steady-state fluorescence intensity information for protein-protein interaction studies.

Findings

Our developed open source software is dedicated to fluorescence lifetime imaging microscopy (FLIM) data obtained from Becker & Hickl SPC-830. FLIM-FRET analyzer includes: a user-friendly interface enabling automated intensity-based segmentation into single cells, time-resolved fluorescence data fitting to lifetime value for each segmented objects, batch capability, and data representation with donor lifetime versus acceptor/donor intensity quantification as a measure of protein-protein interactions.

Conclusions

The FLIM-FRET analyzer software is a flexible application for lifetime-based FRET analysis. The application, the C#. NET source code, and detailed documentation are freely available at the following URL: http://FLIM-analyzer.ip-korea.org.

     

BmuG@Sbase--a microarray database and analysis tool

The manufacture and use of a whole-genome microarray is a complex process and it is essential that all data surrounding the process is stored, is accessible and can be easily associated with the data generated following hybridization and scanning. As part of a program funded by the Wellcome Trust, the Bacterial Microarray Group at St. George's Hospital Medical School (BmuG@S) will generate whole-genome microarrays for 12 bacterial pathogens for use in collaboration with specialist research groups. BmuG@S will collaborate with these groups at all levels, including the experimental design, methodology and analysis. In addition, we will provide informatic support in the form of a database system (BmuG@Sbase). BmuG@Sbase will provide access through a web interface to the microarray design data and will allow individual users to store their data in a searchable, secure manner. Tools developed by BmuG@S in collaboration with specific research groups investigating analysis methodology will also be made available to those groups using the arrays and submitting data to BmuG@Sbase.     

An open source cryostage and software analysis method for detection of antifreeze activity

The aim of this study is to provide the reader with a simple setup that can detect antifreeze proteins (AFP) by inhibition of ice recrystallisation in very small sample sizes. This includes an open source cryostage, a method for preparing and loading samples as well as a software analysis method. The entire setup was tested using hyperactive AFP from the cerambycid beetle, Rhagium mordax. Samples containing AFP were compared to buffer samples, and the results are visualised as crystal radius evolution over time and in absolute change over 30 min. Statistical analysis showed that samples containing AFP could reliably be told apart from controls after only two minutes of recrystallisation. The goal of providing a fast, cheap and easy method for detecting antifreeze proteins in solution was met, and further development of the system can be followed at https://github.com/pechano/cryostage.     

ProteoWizard: open source software for rapid proteomics tools development

SUMMARY: The ProteoWizard software project provides a modular and extensible set of open-source, cross-platform tools and libraries. The tools perform proteomics data analyses; the libraries enable rapid tool creation by providing a robust, pluggable development framework that simplifies and unifies data file access, and performs standard proteomics and LCMS dataset computations. The library contains readers and writers of the mzML data format, which has been written using modern C++ techniques and design principles and supports a variety of platforms with native compilers. The software has been specifically released under the Apache v2 license to ensure it can be used in both academic and commercial projects. In addition to the library, we also introduce a rapidly growing set of companion tools whose implementation helps to illustrate the simplicity of developing applications on top of the ProteoWizard library. AVAILABILITY: Cross-platform software that compiles using native compilers (i.e. GCC on Linux, MSVC on Windows and XCode on OSX) is available for download free of charge, at http://proteowizard.sourceforge.net. This website also provides code examples, and documentation. It is our hope the ProteoWizard project will become a standard platform for proteomics development; consequently, code use, contribution and further development are strongly encouraged.     

Simple Neurite Tracer: open source software for reconstruction, visualization and analysis of neuronal processes

MOTIVATION: Advances in techniques to sparsely label neurons unlock the potential to reconstruct connectivity from 3D image stacks acquired by light microscopy. We present an application for semi-automated tracing of neurons to quickly annotate noisy datasets and construct complex neuronal topologies, which we call the Simple Neurite Tracer. AVAILABILITY: Simple Neurite Tracer is open source software, licensed under the GNU General Public Licence (GPL) and based on the public domain image processing software ImageJ. The software and further documentation are available via http://fiji.sc/Simple_Neurite_Tracer as part of the package Fiji, and can be used on Windows, Mac OS and Linux. Documentation and introductory screencasts are available at the same URL. CONTACT: longair@ini.phys.ethz.ch; longair@ini.phys.ethz.ch.     

Comparative evaluation of microarray analysis software

A wide variety of software tools are available to analyze microarray data. To identify the optimum software for any project, it is essential to define specific and essential criteria on which to evaluate the advantages of the key features. In this review we describe the results of our comparison of several software tools. We then conclude with a discussion of the subset of tools that are most commonly used and describe the features that would constitute the “ideal microarray analysis software suite.”     

OpenChrom: a cross-platform open source software for the mass spectrometric analysis of chromatographic data

Background  

Today, data evaluation has become a bottleneck in chromatographic science. Analytical instruments equipped with automated samplers yield large amounts of measurement data, which needs to be verified and analyzed. Since nearly every GC/MS instrument vendor offers its own data format and software tools, the consequences are problems with data exchange and a lack of comparability between the analytical results. To challenge this situation a number of either commercial or non-profit software applications have been developed. These applications provide functionalities to import and analyze several data formats but have shortcomings in terms of the transparency of the implemented analytical algorithms and/or are restricted to a specific computer platform.     

GENEVESTIGATOR. Arabidopsis microarray database and analysis toolbox

High-throughput gene expression analysis has become a frequent and powerful research tool in biology. At present, however, few software applications have been developed for biologists to query large microarray gene expression databases using a Web-browser interface. We present GENEVESTIGATOR, a database and Web-browser data mining interface for Affymetrix GeneChip data. Users can query the database to retrieve the expression patterns of individual genes throughout chosen environmental conditions, growth stages, or organs. Reversely, mining tools allow users to identify genes specifically expressed during selected stresses, growth stages, or in particular organs. Using GENEVESTIGATOR, the gene expression profiles of more than 22,000 Arabidopsis genes can be obtained, including those of 10,600 currently uncharacterized genes. The objective of this software application is to direct gene functional discovery and design of new experiments by providing plant biologists with contextual information on the expression of genes. The database and analysis toolbox is available as a community resource at https://www.genevestigator.ethz.ch.     

SNPTools: a software tool for visualization and analysis of microarray data

SUMMARY: We have created a software tool, SNPTools, for analysis and visualization of microarray data, mainly SNP array data. The software can analyse and find differences in intensity levels between groups of arrays and identify segments of SNPs (genes, clones), where the intensity levels differ significantly between the groups. In addition, SNPTools can show jointly loss-of-heterozygosity (LOH) data (derived from genotypes) and intensity data for paired samples of tumour and normal arrays. The output graphs can be manipulated in various ways to modify and adjust the layout. A wizard allows options and parameters to be changed easily and graphs replotted. All output can be saved in various formats, and also re-opened in SNPTools for further analysis. For explorative use, SNPTools allows various genome information to be loaded onto the graphs. AVAILABILITY: The software, example data sets and tutorials are freely available from http://www.birc.au.dk/snptools     

cPath: open source software for collecting, storing, and querying biological pathways

Background  

Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required.     

D-MaPs - DNA-microarray projects: Web-based software for multi-platform microarray analysis

The web application D-Maps provides a user-friendly interface to researchers performing studies based on microarrays. The program was developed to manage and process one- or two-color microarray data obtained from several platforms (currently, GeneTAC, ScanArray, CodeLink, NimbleGen and Affymetrix). Despite the availability of many algorithms and many software programs designed to perform microarray analysis on the internet, these usually require sophisticated knowledge of mathematics, statistics and computation. D-maps was developed to overcome the requirement of high performance computers or programming experience. D-Maps performs raw data processing, normalization and statistical analysis, allowing access to the analyzed data in text or graphical format. An original feature presented by D-Maps is GEO (Gene Expression Omnibus) submission format service. The D-MaPs application was already used for analysis of oligonucleotide microarrays and PCR-spotted arrays (one- and two-color, laser and light scanner). In conclusion, D-Maps is a valuable tool for microarray research community, especially in the case of groups without a bioinformatic core.     

R/Bioconductor在Affymetrix表达芯片中的应用

R是用于统计计算和数据作图的编程语言和程序设计环境,能在多种平台下编译和运行。Bioconductor也是免费开源的程序设计环境,它主要基于统计编程语言R,用于基因组数据的分析。我们通过已发表的数据,包含斑马鱼心肌再生的生物芯片数据,分析源码实例,较为详细地介绍和讲解了R/BioConductor的用法,为推广优秀的免费统计软件提供了一个简单的中文使用手册。     

Comparison of different microarray data analysis programs and description of a database for microarray data management

Data analysis and management represent a major challenge for gene expression studies using microarrays. Here, we compare different methods of analysis and demonstrate the utility of a personal microarray database. Gene expression during HIV infection of cell lines was studied using Affymetrix U-133 A and B chips. The data were analyzed using Affymetrix Microarray Suite and Data Mining Tool, Silicon Genetics GeneSpring, and dChip from Harvard School of Public Health. A small-scale database was established with FileMaker Pro Developer to manage and analyze the data. There was great variability among the programs in the lists of significantly changed genes constructed from the same data. Similarly choices of different parameters for normalization, comparison, and standardization greatly affected the outcome. As many probe sets on the U133 chip target the same Unigene clusters, the Unigene information can be used as an internal control to confirm and interpret the probe set results. Algorithms used for the determination of changes in gene expression require further refinement and standardization. The use of a personal database powered with Unigene information can enhance the analysis of gene expression data.     

SiGN-SSM: open source parallel software for estimating gene networks with state space models

SiGN-SSM is an open-source gene network estimation software able to run in parallel on PCs and massively parallel supercomputers. The software estimates a state space model (SSM), that is a statistical dynamic model suitable for analyzing short time and/or replicated time series gene expression profiles. SiGN-SSM implements a novel parameter constraint effective to stabilize the estimated models. Also, by using a supercomputer, it is able to determine the gene network structure by a statistical permutation test in a practical time. SiGN-SSM is applicable not only to analyzing temporal regulatory dependencies between genes, but also to extracting the differentially regulated genes from time series expression profiles. AVAILABILITY: SiGN-SSM is distributed under GNU Affero General Public Licence (GNU AGPL) version 3 and can be downloaded at http://sign.hgc.jp/signssm/. The pre-compiled binaries for some architectures are available in addition to the source code. The pre-installed binaries are also available on the Human Genome Center supercomputer system. The online manual and the supplementary information of SiGN-SSM is available on our web site. CONTACT: tamada@ims.u-tokyo.ac.jp.     

sMOL Explorer: an open source, web-enabled database and exploration tool for Small MOLecules datasets

sMOL Explorer is a 2D ligand-based computational tool that provides three major functionalities: data management, information retrieval and extraction and statistical analysis and data mining through Web interface. With sMOL Explorer, users can create personal databases by adding each small molecule via a drawing interface or uploading the data files from internal and external projects into the sMOL database. Then, the database can be browsed and queried with textual and structural similarity search. The molecule can also be submitted to search against external public databases including PubChem, KEGG, DrugBank and eMolecules. Moreover, users can easily access a variety of data mining tools from Weka and R packages to perform analysis including (1) finding the frequent substructure, (2) clustering the molecular fingerprints, (3) identifying and removing irrelevant attributes from the data and (4) building the classification model of biological activity. AVAILABILITY: sMOL Explorer is an Open Source project and is freely available to all interested users at http://www.biotec.or.th/ISL/SMOL/.